三峡库区库岸堆积层滑坡变形趋势分析

doi:10.19388/j.zgdzdc.2024.148

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Abstract In order to accurately grasp the deformation and development laws of landslides in the accumulation lager on the bank of the Three Gorges Reservoir area, the authors conducted a comprehensive study on landslide deformation trends using the rescaled range method, grey model and optimized generalized regression neural network, based on the landslide deformation monitoring data. The research results show that the Hurst exponent of each monitoring point is greater than 0.5 in the landslide deformation trend discrimination results, indicating a continuous increasing trend of landslide deformation. In the deformation prediction results, with the continuous optimization and combination processing of the GM (1,1)-SFLA GRNN model, the prediction accuracy has been significantly improved, indicating that the model construction process is reasonable. Besides, its prediction shows that landslide deformation will continue to increase. The average relative error of the obtained prediction results is between 1.76% and 1.82%, and the training time is between 52.21 ms and 57.23 ms, which has a better prediction effect. Then, BP neural network and support vector machine were introduced for analogical prediction. The results show that the GM (1,1)-SFRA-GRNN model has relatively higher prediction accuracy and faster training speed compared to BP neural network and support vector machine. Comparing the results of landslide deformation trend discrimination and the results of deformation prediction, the authors found that landslide deformation will continue to increase without convergence trend. The necessity of landslide prevention and control is significant, and the rationality of the two analysis methods is mutually supported, providing certain theoretical support for landslide prevention and control.

Key words： reservoir bank landslide rescaled range method deformation prediction trend analysis

Received: 27 March 2023

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	Articles by authors
	MIAO Yuanliang
	ZHANG Shukun
	MENG Chao

Cite this article:

MIAO Yuanliang,ZHANG Shukun,MENG Chao. Analysis of the deformation trend of landslides in the accumulation layer on the bank of Three Gorges Reservoir area[J]. , 2024, 11(6): 86-92.

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http://journal25.magtechjournal.com/Jwk_dzdc/EN/10.19388/j.zgdzdc.2024.148 OR http://journal25.magtechjournal.com/Jwk_dzdc/EN/Y2024/V11/I6/86

[1] 黄金勇,陈志伟,沈艺璇.库水位下降速率对库岸老滑坡间歇性复活的影响[J].水电能源科学,2020,38(1):147-150.
Huang J Y,Chen Z W,Shen Y X.Effect of water level decline rate on intermittent revival of old landslide on reservoir bank[J].Water Resources and Power,2020,38(1):147-150.
[2] 刘录录,李玉婕.库岸降雨型滑坡发生机制变形特征及处理研究[J].人民长江,2019,50(S1):96-101.
Liu L L,Li Y J.Mechanism analysis of landslide of reservoir bank triggered by rainfall and handling measures[J].Yangtze River,2019,50(S1):96-101.
[3] 李松林,许强,汤明高,等.三峡库区滑坡空间发育规律及其关键影响因子[J].地球科学,2020,45(1):341-354.
Li S L,Xu Q,Tang M G,et al.Study on spatial distribution and key influencing factors of landslides in Three Gorges Reservoir Area[J].Earth Science,2020,45(1):341-354.
[4] 陈才. 三峡库区地质灾害类型和灾害机理研究[J].灾害学,2019,34(2):37-42.
Chen C.Types and mechanism of geological disasters in Three Gorges Reservoir Area[J].Journal of Catastrophology,2019,34(2):37-42.
[5] 代贞伟,魏云杰,侯时平.三峡库区杨家水井滑坡变形失稳机理研究[J].工程地质学报,2016,24(4):527-534.
Dai Z W,Wei Y J,Hou S P.Deformation and failure mechanism of Yangjia Well landslide in Three Gorges Reservoir Area[J].Journal of Engineering Geology,2016,24(4):527-534.
[6] 卫童瑶,殷跃平,高杨,等.三峡库区巫山县塔坪H1滑坡变形机制[J].水文地质工程地质,2020,47(4):73-81.
Wei T Y,Yin Y P,Gao Y,et al.Deformation mechanism of the Taping H1 landslide in Wushan County in the Three Gorges Reservoir Area[J].Hydrogeology & Engineering Geology,2020,47(4):73-81.
[7] 代贞伟,李滨,陈云霞,等.三峡大树场镇堆积层滑坡暴雨失稳机理研究[J].水文地质工程地质,2016,43(1):149-156.
Dai Z W,Li B,Chen Y X,et al.A study of the failure mechanism of rainfall-induced accumulation landslide in the Three Gorges Reservoir Region[J].Hydrogeology and Engineering Geology,2016,43(1):149-156.
[8] 吴丽丽,贺可强,全恩厚,等.树坪滑坡切坡抗滑增稳优化治理数值模拟研究[J].河南理工大学学报:自然科学版,2022,41(4):158-165.
Wu L L,He K Q,Quan E H,et al.Numerical simulation study on optimization treatment of anti sliding and stability enhancement of cut slope of Shuping Landslide[J].Journal of Henan Polytechnic University (Natural Science),2022,41(4):158-165.
[9] 易庆林,文凯,覃世磊,等.三峡库区树坪滑坡应急治理工程效果分析[J].水利水电技术,2018,49(11):165-172.
Yi Q L,Wen K,Qin S L,et al.Analysis on effect of emergency treatment project of Shuping Landslide in Three Gorges Reservoir Area[J].Water Resources and Hydropower Engineering,2018,49(11):165-172.
[10] 汤罗圣,左清军,岳敏,等.基于滑带完整性指标的三峡库区堆积层滑坡失稳破坏判据[J].地质科技通报,2022,41(6):77-84.
Tang L S,Zuo Q J,Yue M,et al.Instability failure criterion of debris landslide in the Three Gorges Reservoir Area based on the sliding zone integrity index[J].Bulletin of Geological Science and Technology,2022,41(6):77-84.
[11] 殷跃平,张晨阳,闫慧,等.三峡水库蓄水运行滑坡渗流稳定和防治设计研究[J].岩石力学与工程学报,2022,41(4):649-659.
Yin Y P,Zhang C Y,Yan H,et al.Research on seepage stability and prevention design of landslides during impoundment operation of the Three Gorges Reservoir,China[J].Chinese Journal of Rock Mechanics and Engineering,2022,41(4):649-659.
[12] 高晨曦,刘艺梁,薛欣,等.三峡库区典型堆积层滑坡变形滞后时间效应研究[J].工程地质学报,2021,29(5):1427-1436.
Gao C X,Liu Y L,Xue X,et al.Study on deformation lag time effect of typical colluvial landslide in Three Gorges Reservoir Area[J].Journal of Engineering Geology,2021,29(5):1427-1436.
[13] 肖婷,殷坤龙,杨背背.三峡库区四方碑滑坡稳定性与变形趋势预测[J].中国地质灾害与防治学报,2018,29(1):10-14.
Xiao T,Yin K L,Yang B B.Stability and deformation trend prediction of the Sifangbei Landslide in the Three Gorges Reservoir[J].The Chinese Journal of Geological Hazard and Control,2018,29(1):10-14.
[14] 黄海峰,易武,刘艺梁,等.滑坡位移预测的SVR-MIV变量筛选方法研究[J].地下空间与工程学报,2016,12(1):213-219.
Huang H F,Yi W,Liu Y L,et al.Study on variables selection using SVR-MIV method in displacement prediction of landslides[J].Chinese Journal of Underground Space and Engineering,2016,12(1):213-219.
[15] 张文远,王祯意,孟楠丁.基准风格资产的收益率长记忆性研究——基于修正的R/S模型[J].经济问题,2014(2):59-63.
Zhang W Y,Wang Z Y,Meng N D.An study on long-term memory of fund style asset yields:Based on modified R/S model[J].On Economic Problems,2014(2):59-63.
[16] 邓小鹏,相兴华,王小敏.涉水滑坡岩土体参数弱化机理及变形预测[J].水力发电,2020,46(9):69-73.
Deng X P,Xiang X H,Wang X M.Weakening mechanism of rock and soil parameters of wading landslide and its deformation prediction[J].Water Power,2020,46(9):69-73.
[17] 冯子帆,成枢,董娟.残差修正的GM(1,1)模型在滑坡位移预测中的应用[J].地理空间信息,2019,17(9):113-115.
Feng Z F,Cheng S,Dong J.Application of residual modified GM(1,1) model in landslide displacement prediction[J].Geospatial Information,2019,17(9):113-115.